Python 'IndexError: index 393126 is out of bounds for axis 1 with size 10 'hatası nasıl düzelir?

from keras.models import Sequential
from keras.layers import Dense
from keras.utils import to_categorical
import numpy as np
from sklearn.model_selection import train_test_split
import matplotlib.pyplot as plt
from sklearn import metrics


dataset = np.genfromtxt('emission_dataset.csv', delimiter=',')
Giris = dataset[1:, 0:2]
Cikis = dataset[1:, 2]


Cikis = to_categorical(Cikis, num_classes=10)


Giris_train, Giris_test, Cikis_train, Cikis_test = train_test_split(Giris, Cikis, test_size=0.5, random_state=1)

Cikis_test = to_categorical(Cikis_test, num_classes=10)

model = Sequential()
model.add(Dense(6, input_dim=2, activation='relu'))
model.add(Dense(6, activation='relu'))
model.add(Dense(6, activation='relu'))
model.add(Dense(10, activation='softmax'))



model.compile(loss='categorical_crossentropy', optimizer='adam', metrics=['accuracy'])
model.summary()


model.fit(Giris_train, Cikis_train, epochs=50, batch_size=6)


Cikis_pred = model.predict(Giris_test)
Cikis_pred = np.argmax(Cikis_pred, axis=1)
print(np.shape(Cikis_pred))


print("Accuracy:", metrics.accuracy_score(Cikis_test, Cikis_pred))

from sklearn.metrics import confusion_matrix
import seaborn as sns
import pandas as pd

cm = confusion_matrix(Cikis_test, Cikis_pred)
index = ['co2','ghgs','hfcs','ch4','nf3','n2o','pfcs','sf6','unspecified','other']
columns = ['co2','ghgs','hfcs','ch4','nf3','n2o','pfcs','sf6','unspecified','other']
cm_df = pd.DataFrame(cm,columns,index)                     
plt.figure(figsize=(10,6)) 
sns.heatmap(cm_df, annot=True,fmt="d")

plt.show()